ArticleBMJ open2020
Early prediction of in-hospital mortality in acute pancreatitis: a retrospective observational cohort study based on a large multicentre critical care database.
Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Metabolic syndrome components individually worsen the outcome of acute pancreatitis: a systematic review and meta-analysis.Frontiers in endocrinology · 2025Pooled it
- Usefulness of Random Forest Algorithm in Predicting Severe Acute Pancreatitis.Frontiers in cellular and infection microbiology · 2022Trial
- Article
- Blood urea nitrogen to albumin ratio as a robust predictor of in-hospital mortality in patients with predicted severe acute pancreatitis: a retrospective multicenter observational study.International journal of surgery (London, England) · 2026Observational
- Nomogram for Predicting Pancreatic Pseudocyst in Hypertriglyceridemic Acute Pancreatitis: A Retrospective Cohort Study.Journal of inflammation research · 2026Article
- Construction and validation of a nomogram for predicting survival in elderly patients with severe acute pancreatitis: a retrospective study from a tertiary center.BMC gastroenterology · 2024Article
- A new in-hospital mortality prediction nomogram for intensive care unit patients with acute pancreatitis.Archives of medical science : AMS · 2024Article
- Development and internal validation of a practical model to predict 30 days mortality of severe acute pancreatitis patients.Annals of medicine · 2023Article
- Development and Validation of a Dynamic Nomogram for Predicting in-Hospital Mortality in Patients with Acute Pancreatitis: A Retrospective Cohort Study in the Intensive Care Unit.International journal of general medicine · 2023Article
- Data Science Trends Relevant to Nursing Practice: A Rapid Review of the 2020 Literature.Applied clinical informatics · 2022Review
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo develop and validate a prediction model for predicting in-hospital mortality in patients with acute pancreatitis (AP).
designA retrospective observational cohort study based on a large multicentre critical care database.
settingAll subject data were collected from the eICU Collaborative Research Database (eICU-CRD), which covers 200 859 intensive care unit admissions of 139 367 patients in 208 US hospitals between 2014 and 2015.
participantsA total of 746 patients with AP were drawn from eICU-CRD. Due to loss to follow-up (four patients) or incomplete data (364 patients), 378 patients were enrolled in the primary cohort to establish a nomogram model and to conduct internal validation. PRIMARY AND SECONDARY OUTCOME MEASURES: The outcome of the prediction model was in-hospital mortality. All risk factors found significant in the univariate analysis were considered for multivariate analysis to adjust for confounding factors. Then a nomogram model was established. The performance of the nomogram model was evaluated by the concordance index (C-index) and the calibration plot. The nomogram model was internally validated using the bootstrap resampling method. The predictive accuracy of the nomogram model was compared with that of Acute Physiology, Age, and Chronic Health Evaluation (APACHE) IV. Decision curve analysis (DCA) was performed to evaluate and compare the potential net benefit using of different predictive models.
resultsThe overall in-hospital mortality rate is 4.447%. Age, BUN (blood urea nitrogen) and lactate (ABL) were the independent risk factors determined by multivariate analysis. The C-index of nomogram model ABL (0.896 (95% CI 0.825 to 0.967)) was similar to that of APACHE IV (p=0.086), showing a comparable discriminating power. Calibration plot demonstrated good agreement between the predicted and the actual in-hospital mortality. DCA showed that the nomogram model ABL was clinically useful.
conclusionsNomogram model ABL, which used readily available data, exhibited high predictive value for predicting in-hospital mortality in AP.
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